Just Published: Changes in Physical Activity among United Kingdom University Students Following the Implementation of Coronavirus Lockdown Measures
What a year it has been, it been quiet on the blog front. Hopefully 2021
I will be co-organising a Special Session at next years Face & Gesture 2018 conference in China! I wanted to share some of the information about the Special Session in this post. The session will be entitled "RGBD-based Kinematic Data Analysis and Evaluation for Clinical Applications".
In recent years, there has been an increased interest in automated methods for detection, analysis and quantification of human motion (e.g. physical activity, performance execution and rehabilitation). This is due to the increased availability of low-cost multi-modality RGBD marker-less capturing devices. These devices are clinically important to allow for assessment in home-based and remote settings by extracting kinematic features for use in post-stroke recovery, fall prevention, and in-house elderly monitoring.
The Special Session will provide one of the first platform for computer vision, machine learning and biomedical researchers to present their research, network and advance the field.
A special session on kinematic data analysis and evaluation for clinical applications will be hosted at the 13th IEEE Conference on Automatic Face and Gesture Recognition in Xi’an China in May 2018.
We solicit high-quality theoretical, empirical and application research papers on the topic of this special session. Papers, following FG guidelines, papers can be submitted through the EasyChair system, then select “RGBSpecialSession” track. Accepted papers will be published in the main conference proceedings.
Daniel Leightley - King’s College London
Boulbaba Ben Amor - IMT Lille Douai/CRIStAL CNRS 9189
Moi Hoon Yap - Manchester Metropolitan University
Pavan Turaga - Arizona State University
Anuj Srivastava - Florida State University
If you have any comments or questions about this Special Session, in the first instance please email daniel.leightley@kcl.ac.uk.